Assignment for Comp 551, Fall 2016, McGill University
The entry point of the program is runner.py, where all the applications can be run by these simple flags :
usage: runner.py [-h] [-lr] [-nv] [-sgd] [-rand] [-erf] [-bag]
[-vot] [-ada] [-svm]
optional arguments:
-h, --help show this help message and exit
-lr, --logistic logistic Regression
-nv, --naive Naive Bayes
-sgd, --sgdclassifier
SGD Classifier
-rand, --randomf Random Forest
-erf, --extrarf Extra Random Forest
-bag, --bagging Bagging Ensemble
-vot, --voting Voting Ensemble
-ada, --adaboost Adaboost
-svm, --svm Linear SVM
K Nearest Neighbors implementation was done in R so use RStudio to run it.
- Jeremy Georges-Filteau - McGill ID : 260713547, [email protected]
- Yu Luo - McGill ID : 260605878, [email protected]
- Koustuv Sinha - McGill ID: 260721248, [email protected]